• DocumentCode
    1629195
  • Title

    Financial trend forecasting with fuzzy chaotic oscillatory-based neural networks (CONN)

  • Author

    Kwong, K.M. ; Wong, Max H Y ; Lee, Raymond S T ; Liu, James N K

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
  • fYear
    2009
  • Firstpage
    1947
  • Lastpage
    1952
  • Abstract
    This paper describes a methodology for financial prediction by using an advanced paradigm from computational intelligence - Chaotic Oscillatory-based Neural Networks (CONN) and aid with fuzzy membership function. The method uses financial market data to predict market trends over a certain period of time. This approach may have a wide variety of applications but from financial forecasting perspective, it can be used to identify and forecast market patterns for providing valuable and useful advices to investors for making investment decisions.
  • Keywords
    financial data processing; fuzzy set theory; investment; neural nets; computational intelligence; financial market data; financial trend forecasting; fuzzy chaotic oscillatory-based neural networks; fuzzy membership function; investment decisions; Biological neural networks; Chaos; Cotton; Economic forecasting; Fuzzy neural networks; Neural networks; Neurons; Oscillators; Predictive models; Wind forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
  • Conference_Location
    Jeju Island
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-3596-8
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2009.5277326
  • Filename
    5277326